Model optimization is concerned about how and why a neural network model can be successfully trained [1]}, [2]}. Specifically, the optimization of a deep model is to determine model parameters to minimize a loss function in general non-convex. The loss function is typically designed based on the understanding of a problem and the requirements of the model, and thus generally includes a performance measure, which is evaluated on the training set, and other constraint terms [3]}.
